Molecular force field parametrization using multi-objective evolutionary algorithms-Reference-Cited by-同舟云学术

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Molecular force field parametrization using multi-objective evolutionary algorithms

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Container-title:Proceedings of the 2004 Congress on Evolutionary Computation (IEEE Cat. No.04TH8753)
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Author:

Mostaghim S.,Hoffmann M.,Konig P.H.,Frauenheim T.,Teich J.

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx5/9256/29383/01330859.pdf?arnumber=1330859

Cited by 22 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Determining Lennard-Jones Parameters Using Multiscale Target Data through Presampling-Enhanced, Surrogate-Assisted Global Optimization;Journal of Chemical Information and Modeling;2023-03-21

2. gmak: A Parameter-Space Mapping Strategy for Force-Field Calibration;Journal of Chemical Theory and Computation;2023-01-12

3. Emerging Era of Biomolecular Membrane Simulations: Automated Physically-Justified Force Field Development and Quality-Evaluated Databanks;The Journal of Physical Chemistry B;2022-06-06

4. Reference Point-Based Particle Sub-Swarm Optimization;2021 IEEE International Conference on Systems, Man, and Cybernetics (SMC);2021-10-17

5. On-the-Fly Training of Atomistic Potentials for Flexible and Mechanically Interlocked Molecules;Journal of Chemical Theory and Computation;2021-10-06

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